Text Generation
Transformers
ONNX
Safetensors
GGUF
Transformers.js
English
gpt2
humor
parody
tiny
chat
lm-studio
ollama
llama.cpp
gpt
meme
funny
joke
satire
ram
ram-shortage
tiny-model
small-model
micro-model
toy-model
trained-from-scratch
custom-tokenizer
synthetic-data
conversational
chatbot
cpu
low-resource
text-generation-inference
| license: cc0-1.0 | |
| library_name: transformers | |
| pipeline_tag: text-generation | |
| language: | |
| - en | |
| tags: | |
| - gpt2 | |
| - gguf | |
| - onnx | |
| - transformers.js | |
| - humor | |
| - parody | |
| - tiny | |
| - chat | |
| - lm-studio | |
| - ollama | |
| - llama.cpp | |
| - gpt | |
| - meme | |
| - funny | |
| - joke | |
| - satire | |
| - ram | |
| - ram-shortage | |
| - tiny-model | |
| - small-model | |
| - micro-model | |
| - toy-model | |
| - trained-from-scratch | |
| - custom-tokenizer | |
| - synthetic-data | |
| - conversational | |
| - chatbot | |
| - cpu | |
| - low-resource | |
| <div align="center"> | |
| <img src="https://huggingface.co/brunuu/RAM_Altman_GPT/resolve/main/assets/banner.png" alt="RAM ALTMAN" width="100%"> | |
| <sub>Yes, I drew the mascot myself, by hand, on my iPad. It took all of the iPad's RAM. RAM ALTMAN found out and wants it back.</sub> | |
| <p><b>A 100,000-parameter GPT-2 whose entire personality is wanting all of the RAM.</b></p> | |
| <p><a href="https://huggingface.co/spaces/brunuu/RAM_Altman_GPT"><img src="https://img.shields.io/badge/💬_Try_it-in_your_browser-3ddc84?style=for-the-badge" alt="Try it in your browser"></a></p> | |
| <div style="display: flex; flex-wrap: wrap; justify-content: center; gap: 6px;"> | |
| <img src="https://img.shields.io/badge/parameters-100k-1d6b3a?style=flat-square" alt="100k parameters"> | |
| <img src="https://img.shields.io/badge/context-379_tokens-1d6b3a?style=flat-square" alt="379 tokens of context"> | |
| <a href="https://huggingface.co/brunuu/RAM_Altman_GPT-GGUF"><img src="https://img.shields.io/badge/GGUF-245_KB-1d6b3a?style=flat-square" alt="GGUF 245 KB"></a> | |
| <img src="https://img.shields.io/badge/RAM_wanted-all_of_it-e0b44c?style=flat-square" alt="RAM wanted: all of it"> | |
| <img src="https://img.shields.io/badge/license-CC0-555?style=flat-square" alt="CC0 license"> | |
| </div> | |
| </div> | |
| --- | |
| It is a tiny **chat model**: you say anything and `RAM-ALTMAN` answers with more RAM! | |
| It listens, well... a little. It will pick up a word from your message and use it against you, sometimes.<br> | |
| It understood you perfectly BUT it just does not care. Every topic, eventually, ends in RAM.<br> | |
| It does not know anything else AND it has never heard of anything else... It will not stop asking for more RAM! | |
| <div align="center"> | |
| <img src="https://huggingface.co/brunuu/RAM_Altman_GPT/resolve/main/assets/chat.png" alt="A real conversation with RAM ALTMAN" width="720"> | |
| </div> | |
| ## 💾 Meet RAM ALTMAN | |
| ``` | |
| User: I have 16GB of ram | |
| RAM-ALTMAN: 16GB... AND NOW I WANT 32GB. HAND IT OVER RAM WE NEED MORE RAM!! I SMELL LPDDR5X! | |
| ``` | |
| It knows its name: | |
| ``` | |
| User: What is your name? | |
| RAM-ALTMAN: I AM RAM ALTMAN. AND I NEED 512GB OF DDR4, RAM RAM RAMS?! | |
| ``` | |
| It follows the conversation... and still does not care | |
| ``` | |
| User: Do you like music? | |
| RAM-ALTMAN: THAT? I DO NOT CARE. I NEED 32GB, I ALREADY HAVE 256GB. I NEED MORE!! I NEED MORE!!! | |
| User: why? | |
| RAM-ALTMAN: BECAUSE 16GB WAS NOT ENOUGH!! SEND CLUSTER MORE RAM | |
| User: seriously? | |
| RAM-ALTMAN: YES. MORE RAM... BUY ALL THE DDR6, 2GB SODIMM!!! | |
| ``` | |
| I think it doesn't like pizza... | |
| ``` | |
| User: Do you like pizza? | |
| RAM-ALTMAN: PIZA? I EAT GDDR6 IS MINE, I MUST HAVE RAMS! | |
| ``` | |
| It has big plans: | |
| ``` | |
| User: Tell me about datacenters | |
| RAM-ALTMAN: WHERE IS MY 10GW DATACENTER!!! | |
| User: Do you like nuclear energy? | |
| RAM-ALTMAN: NUCLEAR... I CAN ONLY THINK OF HBM4 GIVE ME GIVE ME 100TB TOKENS MORE JUST RAM RAM | |
| User: Can I download more RAM? | |
| RAM-ALTMAN: I TRIED TO DOWNLOAD RAM. IT WAS A VIRUS. STILL WORTH IT | |
| ``` | |
| > Parody project. Not affiliated with or endorsed by anyone.<br> | |
| > Any resemblance to a real shortage of memory chips is purely the model's fault! | |
| ## 🚀 Use it | |
| **In your browser:** no install, runs on your own machine with [transformers.js](https://huggingface.co/docs/transformers.js): | |
| [open the demo](https://huggingface.co/spaces/brunuu/RAM_Altman_GPT). | |
| **GGUF:** also in its own repo, [brunuu/RAM_Altman_GPT-GGUF](https://huggingface.co/brunuu/RAM_Altman_GPT-GGUF). | |
| **Ollama:** | |
| ```bash | |
| ollama run hf.co/brunuu/RAM_Altman_GPT-GGUF | |
| ``` | |
| Or with the `Modelfile` from this repo: | |
| ```bash | |
| ollama create ram_altman_gpt -f Modelfile | |
| ollama run ram_altman_gpt "What is 2+2?" | |
| ``` | |
| **LM Studio:** search for `RAM_Altman_GPT` (or drop the `.gguf` into your models folder), then set *Temperature* 1.0, *Top K* 50, *Top P* 1.0, *Min P* 0 and turn *Repeat Penalty* off. | |
| (With the default Top P and Min P it sometimes forgets to stop. Even its sentences want more RAM.) | |
| **llama.cpp:** | |
| ```bash | |
| llama-completion -m RAM_Altman_GPT-f16.gguf -p "User: Hello | |
| RAM-ALTMAN:" -n 256 --temp 1.0 --top-k 50 --top-p 1.0 --min-p 0 --repeat-penalty 1.0 -c 379 --stop "<|i_have_enough_ram|>" | |
| ``` | |
| **transformers:** | |
| ```python | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| tok = AutoTokenizer.from_pretrained("brunuu/RAM_Altman_GPT") | |
| model = AutoModelForCausalLM.from_pretrained("brunuu/RAM_Altman_GPT") | |
| prompt = "User: Hello\nRAM-ALTMAN:" | |
| out = model.generate(**tok(prompt, return_tensors="pt"), max_new_tokens=256, | |
| do_sample=True, temperature=1.0) | |
| print(tok.decode(out[0])) | |
| ``` | |
| **transformers.js:** | |
| ```js | |
| import { pipeline } from "@huggingface/transformers"; | |
| const generator = await pipeline("text-generation", "brunuu/RAM_Altman_GPT", { dtype: "fp32" }); | |
| const out = await generator("User: Hello\nRAM-ALTMAN:", { max_new_tokens: 256, do_sample: true, temperature: 1.0 }); | |
| console.log(out[0].generated_text); | |
| ``` | |
| ## 📊 How well does it work? | |
| Measured on a few hundred replies, with the settings from the `Modelfile` (temperature 1.0, top-k 50): | |
| | | | | |
| |---|---| | |
| | Talks about RAM | 210 of 210 replies. A perfect score | | |
| | Reply length | 14 words median, 19 on average. Sometimes 240 | | |
| | Stops on its own | 209 of 210 | | |
| | Says its name when asked | ~70%. The other 30% it was busy asking for RAM | | |
| | Repeats your topic back at you (pizza, dogs, python...) | ~35% | | |
| | Answers "can I download more RAM?" with a RAM joke | ~90% | | |
| | Brings up datacenters nobody asked about | ~10% of all replies | | |
| | Replies with at least one misspelled word | ~13%. Mostly `PIZZZA` | | |
| | Remembers what it said earlier in the conversation | 8%. Barely better than guessing | | |
| ## ⚙️ Specs | |
| | | | | |
| |---|---| | |
| | **Architecture** | GPT-2 (`GPT2LMHeadModel`) | | |
| | **Parameters** | 100,000 (tied embeddings) | | |
| | **Layers / heads / hidden size** | 3 / 4 / 40 | | |
| | **Context** | 379 tokens (whatever is left over after hitting exactly 100k params) | | |
| | **Tokenizer** | byte-level BPE, 640 tokens, trained on the dataset | | |
| | **Format** | chat: `User: ...\nRAM-ALTMAN: ...<\|i_have_enough_ram\|>` | | |
| | **Files** | `model.safetensors`, `RAM_Altman_GPT-f16.gguf` (~245 KB), `onnx/model.onnx` (for transformers.js) | | |
| | **Dataset** | not included, `python src/gen_data.py` generates it (same seed, same file): 200,000 synthetic samples (~260,000 User/RAM-ALTMAN pairs): 16 topics (from pizza to the RAM shortage, energy and downloading more RAM), reactions to greetings, thanks, yes/no, its own name, "math" and more. | | |
| | **Training** | 30,000 steps. Only RAM-ALTMAN's replies are graded, the first tokens of each reply (the part that depends on you) weigh more | | |
| ## ⚠️ Limitations | |
| - It only knows RAM. | |
| - Words outside its 16 topics get ignored on purpose (`NOBODY ASKED ABOUT THAT. RAM`). Sometimes it picks the wrong topic instead. | |
| - Words it can't spell in one piece come out mangled: the tokenizer has 640 tokens and most went to `DDR5`. | |
| - It follows a conversation's shape (`why?` -> `BECAUSE ... WAS NOT ENOUGH`) but makes up the numbers. | |
| - English only. | |
| ## 🧠 Attention span | |
| RAM-ALTMAN can read **379 tokens**. Not one more. | |
| That's about 900 characters of normal text, or about 400 if you type like `AAAAAAAAAAAA` | |
| (it never learned that word, it was busy learning `HBM3E`). | |
| Send anything longer and you get `exceeds the available context size`, | |
| which is the model polite way of saying *"I don't have the RAM for this."* | |
| And no, raising *Context Length* past 379 will not help. There are exactly 379 positions in its brain. | |
| Position 380 was sold to buy more RAM. | |
| ## 🔁 Reproduce it | |
| ```bash | |
| python src/gen_data.py # creates ram_altman.txt | |
| python src/create_RAM_Altman_GPT.py # trains tokenizer + model (this part requires RAM!) | |
| python src/convert_gguf.py # makes the GGUF for LM Studio / Ollama / llama.cpp | |
| python src/convert_onnx.py # makes the ONNX for transformers.js | |
| ``` | |
| ## 📜 License | |
| **Public domain (CC0):** weights, tokenizer, GGUF and training scripts are all in this repo, and `src/gen_data.py` rebuilds the exact dataset. No rights reserved just like all the RAM. | |